The marketing landscape has drastically evolved in the past two decades. In the early 2000s, digital marketing was still in its infancy, and marketers were grappling with the shift from traditional to online platforms.
The mid to late 2000s saw the rise of Customer Relationship Management (CRM) systems. These tools automated data management and allowed for more targeted, personalized communication with customers. It was a significant leap from manual spreadsheet management, but still required substantial effort and oversight.
The advent of social media platforms further revolutionized the industry, creating new channels for customer engagement and feedback. Yet, even with these technological advancements, the burden of manually creating content, predicting trends, and generating visuals remained.
Now, AI is at the forefront, transforming marketing before our eyes. With capabilities like automated content creation, image generation, advanced forecasting, and more, AI is not just a tool—it's an essential partner for marketers.
Whether you're a seasoned marketing veteran or a newcomer to the field, you can use AI to elevate your business’ marketing efforts, and this eBook will explore some powerful ways to do so.
The challenges of marketing in the digital age have left people looking for ways to make it easier. Companies are now using artificial intelligence to optimize marketing operations, increase ROI, and ensure brand consistency - all towards the goal of faster growth.
AI offers benefits such as automation, marketing measurement, personalization, reducing errors, and making faster decisions that human marketers can't or don’t have the time for. AI has limitless potential to automate tasks and save time across a number of powerful use-cases.
Automation frees up time from repetitive tasks so that marketers can spend more time on developing creative campaigns and strategies to help grow your business.
Practically every business has sections of the customer journey and user acquisition funnel that are brute-forced - places where conversion rates reach just high enough to make sense for the company to invest in driving more volume.
Using AI, marketers can automatically identify the best leads for a business and route them directly to the right people and easily measure the quality of each advertisement channel and turn on and off spend automatically as the ROI approaches a critical threshold. Other roles like operations can parse open-ended text (both customer application input and sales team notes) to automate and optimize each engagement, and salespeople can focus their time and energy on the best contacts that will generate the most revenue – making their jobs massively more efficient.
The benefits of AI in marketing don't stop at reducing workloads: AI also helps you measure your business' success and metrics more effectively.
AI can help you optimize advertising spend by efficiently finding new customers through channel optimization and audience targeting. It identifies the ideal customers based on established patterns and tracks individual ad performance. AI facilitates the understanding of customer behavior through accurate reports generated from data gathered from customer interactions. It also alerts businesses to take action based on the data, such as targeting customers for upsells or preventing churn.
Personalization is another primary use-case of AI in marketing departments. AI-powered personalization will help you find the right message for your target audience on a granular level, leading to better user experiences and higher conversion rates.
AI models can make it easier for marketers and advertisers to personalize content, from product recommendations in email marketing to demographic and firmographic targeted messaging on social media. With AI, digital marketers can create campaigns they know their customers will engage with and, as a result, reduce wasted time and money spent on unproductive channels.
By using algorithms to analyze data about customers’ decisions (ranging from their time on an e-commerce site to their purchasing history), marketers can predict which next piece of content is most likely to result in a customer making a purchase.
Identifying key patterns in your data is challenging and easy to get wrong when done manually, with potentially dramatic consequences. Drawing conclusions from manual data analysis is subject to human bias - and it is very common to use the specific lens that most supports an agenda when presenting findings. These errors in understanding and decision making compound over time and drag down your growth trajectory.
Similarly, it’s easy to make single-customer level mistakes when dealing with a huge volume of data, such as classifying customer support tickets. This can lead to presenting a solution to a customer that’s entirely unrelated to their actual problem, leaving customers frustrated and subject to churn.
Mistakes are human, that’s what makes AI such a great candidate to help. AI marketing can both surface the actual underlying patterns from business data and also automate and streamline repetitive tasks and eliminate all-too-common human error.
These benefits together add up to faster decision-making. Using the power of automation and algorithms, businesses can implement changes more quickly, stamp out process inefficiency and, most importantly, maximize revenue capture.
While the potential applications for artificial intelligence are limitless, one of the essential aspects of any AI endeavor is to ensure that any predictions it makes are aligned with the values of your company and of society. This is just as instrumental in the future of digital marketing.
There are also considerations surrounding data quantity and quality, consent and privacy, bias, and technical details that need to be taken into account when developing marketing automation systems or applications.
The quantity and quality of data used to train AI models directly impact the accuracy of predictions. Insufficient data may require obtaining more information, such as exporting and labeling relevant data from existing systems.
Having a larger dataset generally improves model performance by capturing a wider range of inputs and outcomes. Companies can also enhance their data by integrating third-party sources or merging data from multiple channels using ML platform features.
Companies that collect, analyze, and use data and ML to operate their business have to maintain the trust of their users. Leading companies using ML believe individuals should have control and transparency over their data.
Their data should not be sent or disclosed to another individual or organization unless the user has given explicit consent to do so. And personally identifiable data should not be used for purposes outside of benefiting the user without permission from the user.
When deploying AI automation, marketers need to be aware of the biases that can be perpetuated by using historical data to predict future outcomes. It is important to proactively identify and eliminate biases that negatively impact certain groups. ML platforms can help marketers identify influential factors and decide whether they should be considered in the model, allowing them to exclude biased data if necessary.
Companies should consider which types of AI models they want to invest in for their predictive analytics and marketing processes, as there are endless opportunities when it comes to AI and data science.
The most common types of models that marketers choose are Classification and Time-Series Forecasting. Companies should decide how they want to implement these AI models into their marketing tools: at an individual or enterprise level, as well as what specific goal they want to focus on using the AI model for - whether it's conversions, engagements, or clicks.
The world of SEO content is fiercely competitive, with millions of articles published daily, and websites vying for the top positions on search engine results pages (SERPs). In this competitive landscape, producing high-quality content alone is not enough.
Content creators must also ensure that their content is optimized for search engines, addressing factors like keyword targeting, on-page optimization, and backlinks. This optimization process is often resource-intensive and time-consuming, leading to inconsistent performance that frustrates clients and hinders the success of content marketing campaigns.
Tools like Akkio can help digital marketers and SEO specialists build AI to target high-performing keywords more accurately, and vastly improve their content rankings on search results. Learn more about how marketing agency, Ellipsis, was able to 4x their clients’ SEO results with Akkio.
With augmented lead scoring, marketers can effortlessly discover which sources are generating leads with the highest purchase intent (or other desired action).
This enables marketers to adjust the marketing funnel and spend quickly and efficiently, rather than waiting for infrequent and out-of-date reviews and recaps. Akkio makes lead scoring simple by enabling marketers to upload CRM data through a spreadsheet, or connect directly to their Hubspot or Salesforce.
From there, you can train and build an AI model in minutes, without technical expertise, and start predicting the scores of future leads. Ultimately, this lets both marketing and sales teams prioritize the most important leads.
Many businesses have large sales funnels that allow them to expansively capture leads and nurture them into more sales. With the wealth of customer data available, it’s possible to customize the entire process based on previous purchase history. Many businesses are using AI in marketing to take customers through a personalized journey down the sales funnel.
Sales funnel optimization (SFO) is a great way to make your sales job easier, find sticking points in the funnel, and ultimately close more deals. Companies armed with AI-powered SFO will naturally have an advantage over their competitors that are stuck using inefficient manual or often incorrect rules-based methods.
Predicting what and when your customers will purchase helps with your planning at all levels of a business. This level of foresight allows you to focus your business accordingly.
Traditional forecasting takes a lot of time-consuming manual work, data engineering, and needs statistical expertise. AI makes forecasting effortless, even for non-technical teams, allowing marketers to plan ahead, predict campaign performance, and build better budgets.
With Akkio’s forecasting, sales and marketing teams no longer need to guess what sales will be for the next year. You can quickly understand patterns, analyze influential factors, and make a time series model to predict future results.
Many businesses focus on generating leads and closing new business while forgetting that minimizing churn is just as important. If lead generation is plateauing, but churn is still a problem (as it is for most businesses), then your business will inevitably start losing capital.
With Akkio, marketing teams can build churn prediction models to find which customers are most likely to churn next and turn that into action. Teams can reach out with targeted attention or solutions to save those customers. And in the longer term, the marketing analytics they gain from this activity can help businesses fix the underlying causes of churn.
Traditional artificial intelligence software solutions require a lot of time and technical expertise. With Akkio, marketing teams get access to cutting-edge technology in an easy, affordable way. Now, even non-technical marketing teams can grow their businesses with AI beyond what they ever thought was possible.
AI helps marketers optimize their ads, score leads, forecast sales, and more. Perhaps even more importantly, AI helps marketers automate the boring work, allowing teams to focus on strategic and creative tasks.
Sign up for a free trial of Akkio to experience first-hand how AI can transform your marketing efforts.